Mlops Engineer (Clone)

₹20L – ₹30L
|
Remote •
India
|2 years of exp
|Full Time

Posted: 4 months ago

Visa Sponsorship

Not Available

Remote Work Policy

Remote only

Hires remotely

Everywhere

RelocationNot Allowed

Skills

AWS/EC2/ELB/S3/DynamoDB

AWS Cloud Services

Apache/Spark/Databricks

Airflow

H20/Tensorflow /Caffe

Apache Airflow

Kubeflow

MLFlow

AWS SageMaker

Azure Databricks

Scala, Java, Python, Sql, Etl, Hadoop, Apache Spark, Apache Airflow, Docker

Platforms : Kubernetes, Kubeflow, Kubeless, Flowable, Kafka, Argo

DataOps

MLOps

AWS EC2/S3/Sagemaker

ETL (Apache Airflow)

Azure MLFlow

Python, SQL,AWS, Kubeflow, PyTorch, TensorFlow, Keras, Django, Kafka

Azure MLOps

Python, PySpark, PyTorch, MLFlow, SQL, AWS EC2/ECR/Batch, Bash, Docker, C/C++

MLOPs(Azure DevOps, Mlflow, Kedro, Airflow, Tfx, Evidently, Dataiku, Dvc, Github Acti

Python, SQL, AWS, Kubeflow, TensorFlow, Kubernetes, Machine Learning, Deep Learning,

MLOps: MLFlow, SageMaker, HuggingFace

MLOps, DevOps, DataOps, SDLC, Agile, TDD, Jenkins, Git, BitBucket, Jupyter Notebook,

Hiring contact

Harsha K

About the job

Responsibility:
● Infrastructure Setup and Maintenance: Design, deploy, and maintain scalable and reliable infrastructure for machine learning model deployment and operations
● Automating and orchestrating the CI/CD process of the organization
● Model Deployment and Monitoring : Work closely with data scientists to troubleshoot and address
issues related to model performance and scalability.
● Managing cloud environments in accordance with company security guidelines
● Stay current with industry trends, making recommendations as needed to help the company excel
● Develop reporting for cloud-based environments to meet the security, performance, and monitoring
requirements
● Performance analysis, proactive troubleshooting and capacity planning
● Other duties as assigned
Preferred Skill sets:
● Hands-on experience on cloud platforms (e.g., AWS, Azure, GCP) with VPC, Load balancer, VM,
SQL, Storage
● Knowledge of Configuration Management tools like – Puppet, Ansible, Chef, Terraform, etc.
● Proven experience as a DevOps or MLOps Engineer, with a focus on machine learning
deployments.
● Strong proficiency in scripting languages (e.g., Python, Bash)
● Knowledge of Linux operating system
● Knowledge of CI/CD tools like Jenkins
● Hands-on experience with containerization and orchestration tools (e.g.,Docker, Kubernetes).
● Excellent problem-solving and communication skills.